PHP code example of frolaxhq / laravel-llm-tokenkit

    
        
<?php
require_once('vendor/autoload.php');

/* Start to develop here. Best regards https://php-download.com/ */

    

frolaxhq / laravel-llm-tokenkit example snippets

use Frolax\LlmTokenKit\Facades\LlmTokenKit;
use Frolax\LlmTokenKit\Data\ModelRef;

$model = new ModelRef(provider: 'openai', model: 'gpt-4o');

// Or use a simple array:
$model = ['provider' => 'openai', 'model' => 'gpt-4o'];

$estimate = LlmTokenKit::estimateText('Hello, world!', $model);

$estimate->inputTokensEstimated; // ~4
$estimate->confidence;           // Confidence::Medium
$estimate->method;               // EstimationMethod::Heuristic
$estimate->notes;                // ['...']

$messages = [
    ['role' => 'system', 'content' => 'You are a helpful assistant.'],
    ['role' => 'user', 'content' => 'What is Laravel?'],
];

$estimate = LlmTokenKit::estimateMessages($messages, $model);

$estimate->inputTokensEstimated; // ~18

use Frolax\LlmTokenKit\Data\TokenUsage;

$cost = LlmTokenKit::cost(
    usage: new TokenUsage(promptTokens: 1500, completionTokens: 500),
    model: $model,
);

$cost->inputCost;   // 0.00375
$cost->outputCost;  // 0.005
$cost->totalCost;   // 0.00875
$cost->currency;    // 'USD'

$cost = LlmTokenKit::cost(
    usage: ['prompt_tokens' => 1500, 'completion_tokens' => 500],
    model: ['provider' => 'openai', 'model' => 'gpt-4o'],
);

use Frolax\LlmTokenKit\Data\Pricing;

$cost = LlmTokenKit::cost(
    usage: new TokenUsage(promptTokens: 1000, completionTokens: 200),
    pricing: new Pricing(inputPer1m: 15.00, outputPer1m: 60.00, reasoningPer1m: 60.00),
);

use Frolax\LlmTokenKit\Data\ContextBuildRequest;
use Frolax\LlmTokenKit\Enums\ContextStrategy;

$result = LlmTokenKit::buildContext(new ContextBuildRequest(
    system: 'You are a helpful assistant.',
    memorySummary: 'User prefers dark mode.',
    historyMessages: $chatHistory,
    newUserMessage: 'How do I use Eloquent?',
    modelRef: $model,
    tokenBudget: 4000,
    reservedOutputTokens: 1024,
    strategy: ContextStrategy::TruncateByTokens,
));

$result->messages;            // Ready-to-send message array
$result->tokenEstimate;       // TokenEstimate DTO
$result->wasTruncated;        // true if messages were dropped
$result->droppedMessageCount; // Number of dropped messages
$result->warnings;            // Any warnings

$result = LlmTokenKit::buildContext([
    'system' => 'You are helpful.',
    'history_messages' => $chatHistory,
    'new_user_message' => 'Hello!',
    'model_ref' => ['provider' => 'openai', 'model' => 'gpt-4o'],
    'token_budget' => 4000,
    'strategy' => 'truncate_by_tokens',
]);

// config/llm-tokenkit.php
'pricing' => [
    'default' => [
        'input_per_1m' => 1.00,
        'output_per_1m' => 2.00,
        'currency' => 'USD',
    ],
    'providers' => [
        'openai' => [
            'models' => [
                'gpt-4o' => ['input_per_1m' => 2.50, 'output_per_1m' => 10.00],
                'gpt-4.1*' => ['input_per_1m' => 2.00, 'output_per_1m' => 8.00],
            ],
            'default' => ['input_per_1m' => 2.50, 'output_per_1m' => 10.00],
        ],
    ],
],

'estimation' => [
    'code_json_penalty' => 1.3,       // Multiplier for code/JSON
    'enable_code_json_penalty' => true,
    'language_multipliers' => [
        'bn' => 2.5,  // Bangla
        'hi' => 2.0,  // Hindi
        'ar' => 2.0,  // Arabic
        'zh' => 1.5,  // Chinese
    ],
],

'context' => [
    'reserved_output_tokens' => 4096,
    'window_size' => 50,
    'default_strategy' => 'rolling_window',
    'tool_token_threshold' => 200,
],

bash
php artisan vendor:publish --tag="llm-tokenkit-config"

bash
php artisan tokenkit:check